Editing Neural Darwinism (section)

== Population thinking – somatic selective systems ==
[[File:AntibodyChains.svg|thumb|Illustration of disulfide bridges (red) linking the light (L, green) and heavy (H, purple) chains of Immunoglobulin G (IgG) antibody. The variable (V) regions are located at the antigen-binding end; and, the constant (C) domains form the primary frame of the IgG molecule.  Another disulfide bridge holds the two symmetrical units made up of a light chain (V<sub>L</sub>+C<sub>L</sub>) and a heavy chain (V<sub>H</sub>+C<sub>H</sub>1+C<sub>H</sub>2+C<sub>H</sub>3) together to form the completed antibody.{{efn|Work by Rodney Porter with the enzyme [[papain]] resulted in cleavage of the antibody into [[fragment antigen-binding|Fab]] and [[fragment crystallizable region|Fc]] fragments, while work by Gerald Edelman lead to the reduction of the disulfide bridges so as to separate the molecule into light- and heavy-chain fragments.  Together, this work allowed the antibody structure to be sequenced and reconstructed, resulting in the awarding of the Nobel Prize in Physiology or Medicine in 1972.}}]]
[[File:Clonal selection.svg|thumb|left|'''Clonal selection theory''' (CST): [[hematopoietic stem cell]]s (1) differentiate and undergo genetic rearrangement to produce a population of cells possessing a wide range of pre-existing diversity with respect to antibody expression (2).  Lymphocytes expressing antibodies that would lead to autoimmunity are filtered from the population (3), while the rest of the population represents a degenerate pool of diversity (4) where antigen-selected variants (5) can be differentially amplified in response (6).  Once the antigen has been cleared, the responding population will decrease, but not by as much as it was amplified, leaving behind a boosted capacity to respond to future incursions by the antigen – a form of enhanced recognition and memory within the system.]]
Edelman was inspired by the successes of fellow Nobel laureate{{sfn|Burnet|Medawar|1960}} [[Frank MacFarlane Burnet]] and his [[clonal selection]] theory (CST) of acquired [[antigen]] immunity by differential amplification of  pre-existing variation within the finite pool of [[lymphocytes]] in the [[immune system]]. The population of variant lymphocytes within the body mirrored the variant populations of organisms in the ecology. Pre-existing diversity is the engine of adaption in the evolution of populations.

<blockquote>"It is clear from both evolutionary and immunological theory that in facing an unknown future, the fundamental requirement for successful adaption is preexisting diversity".{{sfn|Mountcastle|Edelman|1978|p=56}} – Gerald M. Edelman (1978)</blockquote>

Edelman recognizes the explanatory range of Burnet's utilization of Darwinian principles in describing the operations of the immune system - and, generalizes the process to all cell populations of the organism.  He also comes to view the problem as one of [[Pattern recognition (psychology)|recognition]] and [[memory]] from a biological perspective, where the distinction and preservation of [[self]] vs. [[Immunology#Theoretical immunology|non-self]] is vital to organismal integrity.

Neural Darwinism, as TNGS, is a theory of neuronal group selection that retools the fundamental concepts of Darwin and Burnet's theoretical approach. Neural Darwinism describes the development and evolution of the mammalian brain and its functioning by extending the Darwinian paradigm into the body and nervous system.

=== Antibodies and NCAM – the emerging understanding of somatic selective systems ===

Edelman was a medical researcher, [[physical chemist]], immunologist, and aspiring neuroscientist when he was awarded the 1972 [[Nobel Prize in Physiology or Medicine]] (shared with [[Rodney Porter]] of Great Britain). Edelman's part of the prize was for his work revealing the chemical structure of the vertebrate [[antibody]] by cleaving the covalent [[disulfide]] bridges that join the component chain fragments together, revealing a pair of two-domain light chains and four-domain heavy chains. Subsequent analysis revealed the terminal domains of both chains to be variable domains responsible for antigen recognition.{{sfn|Edelman|1972}}

The work of Porter and Edelman revealed the molecular and genetic foundations underpinning how antibody diversity was generated within the immune system.  Their work supported earlier ideas about pre-existing diversity in the immune system put forward by the pioneering Danish immunologist [[Niels K. Jerne]] (December 23, 1911 – October 7, 1994); as well as supporting the work of Frank MacFarlane Burnet describing how lymphocytes capable of binding to specific foreign antigens are differentially amplified by clonal multiplication of the selected preexisting variants following antigen discovery.

Edelman would draw inspiration from the mechano-chemical aspects of antigen/antibody/lymphocyte interaction in relation to recognition of self-nonself; the degenerate population of lymphocytes in their physiological context; and the bio-theoretical foundations of this work in Darwinian terms.

By 1974, Edelman felt that immunology was firmly established on solid theoretical grounds descriptively, was ready for quantitative experimentation, and could be an ideal model for exploring evolutionary selection processes within an observable time period.{{sfn|Edelman|1974}}

His studies of immune system interactions developed in him an awareness of the importance of the cell surface and the membrane-embedded molecular mechanisms of interactions with other cells and substrates. Edelman would go on to develop his ideas of topobiology around these mechanisms – and, their genetic and epigenetic regulation under the environmental conditions.

During a foray into molecular embryology and neuroscience, in 1975, Edelman and his team went on to isolate the first neural [[cell-adhesion molecule]] (N-CAM), one of the many molecules that hold the animal nervous system together. N-CAM turned out to be an important molecule in guiding the development and differentiation of neuronal groups in the nervous system and brain during [[embryogenesis]]. To the amazement of Edelman, genetic sequencing revealed that N-CAM was the ancestor of the vertebrate antibody{{sfn|Edelman|1987a}} produced in the aftermath of a set of whole genome duplication events at the origin of vertebrates{{sfn|Dehal|Boore|2005}} that gave rise to the entire super-family of [[immunoglobulin genes]].

Edelman reasoned that the N-CAM molecule which is used for self-self recognition and adherence between neurons in the nervous system gave rise to their evolutionary descendants, the antibodies, who evolved self-nonself recognition via antigen-adherence at the origins of the vertebrate antibody-based immune system. If clonal selection was the way the immune system worked, perhaps it was ancestral and more general – and, operating in the embryo and nervous system.

=== Variation in biological systems – degeneracy, complexity, robustness, and evolvability ===
[[File:06 chart pu3.png|thumb|The degeneracy of the genetic code buffers biological systems from the effects of random [[mutation]]. The ingenuous 1964 [[Nirenberg and Leder experiment]] would identify the [[mRNA]] [[codons]], a triplet sequence of [[ribonucleotides]], that coded for each [[amino acid]]; thus elucidating the [[universal genetic code]] within the [[DNA]] when the [[Transcription (biology)|transcription]] process was taken into account. Changes in the third position of the codon, the [[wobble position]], often result in the same amino acid, and oftentimes the choice comes down to [[purine]] or [[pyrimidine]] only when a choice must be made.  Similar, but variant, codon sequences tend to yield similar classes of amino acid – [[Chemical polarity|polar]] to polar, [[Chemical polarity#Nonpolar molecules|non-polar]] to non-polar, [[acidic]] to acidic, and [[Base (chemistry)|basic]] to basic residues.]]
[[File:Overview proteinogenic amino acids-ENG.svg|thumb|The four major classes of biological amino acids – polar (hydrophilic), nonpolar (hydrophobic), acidic, and basic side chain residues.  The amino acid backbone is [[amino]] group linked to an [[alpha carbon]], on which resides the side chain residue and a hydrogen atom, that is connected to a terminal [[carboxylate]] group. Aside from the disulfide bridge, there are quite a number of degenerate combinations of sidechain residues that make up the [[tertiary structure]] ([[H-bonding]], [[hydrophobic]], and [[ionic bridge]]s) in the determination of protein structure.]]
[[File:Relationships between degeneracy, complexity, robustness, and evolvability.png|thumb|left|Relationships between degeneracy, complexity, robustness, and evolvability – 1) degeneracy is the source of robustness. 2) degeneracy is positively correlated with complexity. 3) degeneracy increases evolvability. 4) evolvability is a prerequisite for complexity. 5) complexity increases to improve robustness. 6) evolvability emerges from robustness.]]

Degeneracy, and its relationship to variation, is a key concept in neural Darwinism. The more we deviate from an ideal form, the more we are tempted to describe the deviations as imperfections. Edelman, on the other hand, explicitly acknowledges the structural and dynamic variability of the nervous system. He likes to contrast the differences between redundancy in an engineered system and [[Degeneracy (biology)|degeneracy]] in a biological system. He proceeds to demonstrate how the "noise" of the computational and algorithmic approach is actually beneficial to a somatic selective system by providing a wide, and degenerate, array of potential recognition elements.{{sfn|Tononi|Sporns|Edelman|1999}}

Edelman's argument is that in an engineered system,

* a known problem is confronted
* a logical solution is devised
* an artifice is constructed to implement the resolution to the problem

To insure the robustness of the solution, critical components are replicated as exact copies. Redundancy provides a fail-safe backup in the event of catastrophic failure of an essential component but it is the same response to the same problem once the substitution has been made.

If the problem is predictable and known ahead of time, redundancy works optimally. But biological systems face an open and unpredictable arena of spacetime events of which they have no foreknowledge of. In this arena, redundancy fails - a response might be designed to the wrong problem.

Variation fuels degeneracy; degeneracy provides somatic selective systems with more than one way to solve a problem and the propensity to reuse a solution on other problems. This property of degeneracy makes the system more adaptively robust in the face of unforeseen contingencies: When one particular solution fails unexpectedly, there are other unaffected pathways that can be engaged in pursuit of the same end. Early on, Edelman spends considerable time contrasting degeneracy vs. redundancy, bottom-up vs. top-down processes, and selectionist vs. instructionist explanations of biological phenomena.

=== Rejection of computational models, codes, and point-to-point wiring ===

Edelman was well aware of the earlier debate in immunology between the instructionists, who believed the lymphocytes of the immune system learned or was instructed about the antigen and then devised a response; and the selectionists, who believed that the lymphocytes already contained the response to the antigen within the existing population that was differentially amplified within the population upon contact with the antigen. And, he was well aware that the selectionist had the evidence on their side.

Edelman's theoretical approach in ''Neural Darwinism'' was conceived of in opposition to top-down algorithmic, computational, and instructionist approaches to explaining neural function. Edelman seeks to turn the problems of that paradigm to advantage instead; thereby highlighting the difference between bottom-up processes like we see in biology vis a vis top-down processes like we see in [[engineering]] algorithms. He sees [[neurons]] as living organisms working in cooperative and competitive ways within their local [[ecology]] and rejects models that see the brain in terms of [[computer chip]]s or [[logic gate]]s in an algorithmically organized [[machine]].

Edelman's commitment to the Darwinian underpinnings of biology, his emerging understanding of the evolutionary relationships between the two molecules he had worked with, and his background in immunology lead him to become increasingly critical and dissatisfied with attempts to describe the operation of the nervous system and brain in computational or algorithmic terms.

Edelman explicitly rejects computational approaches to explaining biology as non-biological. Edelman acknowledges that there is a conservation of phylogenetic organization and structure within the vertebrate nervous system, but also points out that locally natural diversity, variation and degeneracy abound. This variation within the nervous system is disruptive for theories based upon strict point-to-point connectivity, computation, or logical circuits based upon codes.  Attempts to understand this ''noise'' present difficulties for top-down algorithmic approaches – and, deny the fundamental facts of the ''biological'' nature of the problem.

Edelman perceived that the problematic and annoying noise of the computational circuit-logic paradigm could be reinterpreted from a population biology perspective – where that variation in the [[signal]] or architecture was actually the engine of ingenuity and robustness from a selectionist perspective.